Codemotion

This is a PRE-SALE ACTIVITY. Preferably to be arranged free of charge


Position name: Technical Consultant — LLM/RAG Architecture 
Level: Senior / Principal / Architect

Hard skills requirements (including years):

• Production experience designing and running RAG pipelines: chunking, embeddings, vector databases, retrieval, reranking, evaluation
• Audio/video processing pipelines: transcription (ASR), speaker diarization, timestamp indexing, handling multi-participant content
• Multi-model / tiered routing architecture — routing lightweight tasks to cheap high-throughput models and escalating complex reasoning tasks to flagship models
• Hands-on evaluation and benchmarking of LLM providers, including Chinese providers (DeepSeek, Alibaba Qwen, ByteDance Doubao, Zhipu GLM, Moonshot Kimi) alongside Western frontier models
• LLM FinOps: token-level cost modelling, unit economics per processing run, and cost projection across a growth curve (10K → 175K → 400K users)
• Capacity and throughput planning: rate limits, batching, caching, concurrency at enterprise volume
• Awareness of the risks of Chinese LLM providers: data residency, compliance, latency outside China, vendor lock-in

Position name: Senior Frontend Developer
Level: Senior

Hard skills requirements (including years):

• Expert TypeScript / JavaScript and React — strong commercial frontend engineering at Senior/Expert level
• Strong Next.js experience and deep understanding of modern frontend architecture
• Demonstrable experience with agentic / AI-assisted software development in real delivery environments — NOT vibe coding; includes appropriate testing, validation and engineering controls
• Automated testing: Playwright for E2E, Jest / Vitest or equivalent for unit/component testing
• GitHub / GitHub Actions and modern CI/CD workflows
• Security-conscious engineering approach, particularly for sensitive / regulated / digital-asset environments
• Web3 / blockchain experience strongly preferred; strong FinTech or financial services background accepted as alternative where candidate demonstrates technical curiosity and ability to ramp quickly
• Ability to shape solutions from high-level or partially defined requirements without heavily specified tickets
• Contribute to frontend architecture and technical design decisions
• Technical guidance and mentoring to another frontend engineer (without formal line management responsibility)

Soft skills requirements:

• Pragmatic, entrepreneurial and product-minded approach
• Comfort challenging assumptions and constructively calling out poor technical or product decisions
• Strong engineering judgement in underspecified environments
• Sociable, collaborative style suited to a close-knit distributed team
• User-focused mindset and pride in crafting high-quality experiences

Key responsibilities:

• Deliver senior-level frontend features across the company's product estate
• Develop scalable, maintainable interfaces using TypeScript, React and Next.js
• Help establish mature agentic / AI-assisted development patterns and engineering controls
• Test own code thoroughly — unit/component and E2E — and collaborate with QA
• Proactively identify Web3 and application-security edge cases
• Provide technical guidance and mentoring to the Cayman-based frontend engineer
• Research unfamiliar product or Web3 topics independently and propose pragmatic solutions

2-3+ years technical leadership experience (team lead / early-stage engineering manager) - HARD MUST
Solid Golang - real production experience (HARD MUST)
Proven Claude Code experience with specific examples

Requirements

Position name: Team Lead, AI Product Engineering
Level: Senior / Tech Lead

Hard skills requirements (including years):

• 2-3+ years of technical leadership experience leading a team, squad, pod, or similar unit (HARD MUST — think team lead or early-stage engineering manager)
• Developer background with 5+ years minimum — seen production reality before moving towards leading people
• Solid Golang experience: real production experience, not just personal projects (HARD MUST — no flexibility on other technologies)
• Proven experience using Claude Code as a core part of development workflow — share specific examples
• AI/backend engineering: deep knowledge of building and productionizing complex AI systems — observability, reliability, quality
• Product-driven mindset: ability to think beyond engineering toward product outcomes and user value
• Comfort facilitating and coordinating a pod without relying on formal authority
• Excellent spoken and written English for planning sessions, stakeholder updates and client conversations
• Ownership mentality — you test your own work thoroughly (no QA team)
• Ability to do on-call when needed to help maintain platform reliability & uptime
• European or African timezones (±3 hours from CET) — mandatory
• Available full-time (40 hours/week)

Soft skills requirements:

• Energized by product planning sessions — has opinions about what the pod should build next, not just how
• Comfortable being the face of the pod, in internal planning rooms and on calls with enterprise clients
• Enjoys enabling engineers who are technically stronger than you
• Ships fast but always verifies it actually works — QA ownership expected
• Gets frustrated when development takes weeks instead of days
• Made the conscious decision to lead people, clients and product — not the lifelong specialist path

Key responsibilities:

• Be the spokesperson for your pod, internally with product, design and leadership, and externally with clients and partners
• Coordinate work across the pod: break initiatives into chunks, sequence them, surface blockers and facilitate hand-offs
• Gather client requirements first-hand and funnel them straight into the pod so nothing gets lost in translation
• Represent your pod in product planning sessions and bring a strong product-driven point of view to scoping and trade-offs
• Help pod members with product decisions and prioritisation, enabling engineers who may be technically stronger
• Contribute hands-on as an engineer: own features end-to-end, use Claude Code to generate Golang backend code, review AI output for quality and architectural fit
• Join client meetings to align on requirements, report on delivery and keep the relationship professional and calm

Office/Remote: Remote

English: Upper-Intermediate+ (client-facing, mandatory)

Time zone: ±3 hours from CET (EU, Ukraine, African timezones)

Strong communication skills is a must - developer should be responsive, answer and ask quetsions and show his thinking process.

Requirements

Position Name: Senior Full-Stack Developer
Level: Senior

Hard skills requirements:

• Python (backend), Vue + TypeScript (frontend) — full-stack, end-to-end delivery
• AI API integrations: RAG, vector search, LLM APIs
• PostgreSQL, SQL and NoSQL databases
• Docker, AWS cloud deployment
• Data visualization: D3.js, Shadcn, Treemaps
• API integrations (email providers: Sendmail, Mailgun, etc.)
• Comfortable working in existing large codebase
• Accountable for AI-generated code — can explain, debug, and optimize it

Soft skills requirements:

• Strong communication — can discuss past projects in technical detail, ask and answer questions clearly
• Logical problem-solving — able to break down vague requirements
• Proactivity and ownership

English: Upper-Intermediate or higher — must have, critical requirement
Office/Remote: Remote. Must be available 8am–2pm PT (Pacific Time), 40 hrs/week

Nice to have

* Experience with AI/ML platforms or news aggregation products * Experience building products for investors or financial/tech professionals * Familiarity with agentic AI development workflows

Main requirements

Snowflake Experience

The person should be proactive, well-organized, and an effective communicator, able to independently drive tasks forward, keep processes under control, and communicate clearly with the team and stakeholders.

Requirements

Senior Data Enginer

Snowflake — core development

• Writing and maintaining production views, secured views and stored logic in Snowflake
• Understanding of role-based access control: users, roles, GRANTs, warehouse and database entitlement models
• Enough query-tuning instinct to build views over large fact tables without wrecking performance — partition pruning, clustering awareness, avoiding SELECT *

Microsoft SQL Server

• T-SQL development
• Migrating legacy tables, views and stored procedures to Snowflake

Previous ETL Tooling Experience

Bonus Points

BI and semantic layer

• Sigma Computing — connection setup, workbooks, embedding, AI/Cortex configuration. We are rolling Sigma out now and retiring Tableau Desktop.
• Tableau — data source management, extract vs live strategy, extract scheduling and dependency mapping

Documentation and code review

• Producing data-flow and architecture diagrams
• Reviewing SQL/pipeline code to a standard — we have a code review backlog in other areas because there aren’t enough qualified SQL reviewers. A contractor who can act as a second reviewer is disproportionately valuable.

Azure DevOps (aka ADF Pipelines sync’d with Github)

• CI/CD pipelines for database and ADF artefacts, service principal / client secret configuration, release troubleshooting

External API ingestion

• Consuming and loading third-party APIs into the warehouse (e.g. FX/exchange rate feeds), including auth and error handling
• Snowflake Git integration — connecting a Git repository to Snowflake, versioning database objects and deploying from a branch, plus general source-control discipline for SQL and pipeline code
• Snowflake Streamlit — building lightweight in-warehouse data apps as an alternative to a full BI workbook where the audience is small or the use case is operational
• Python for data engineering and Snowpark
• Snowflake Cortex / LLM-in-warehouse features
• dbt or equivalent transformation tooling (not in use today, but relevant if we modernise)

Working attributes we need

• Comfortable being the second pair of hands on a one-person team — takes a ticket end-to-end without daily direction
• Documents as they go; we are explicitly trying to reduce single-person key-man risk
• Cost-aware: several of our decisions are spend-driven, not purely technical

English - Andvanced

Main requirements

dbt, Google BigQuery, Python, SQL, Git

Requirements

Position name: Data Engineer (Mid-Level)

Level: Mid-Level

Hard skills requirements:

• Hands-on experience with dbt (models, tests, documentation)
• Experience with Google BigQuery
• Solid Python skills for data engineering
• Strong SQL and data modeling
• Production data pipeline experience
• Git and collaborative development workflows

Soft skills requirements:

• Strong English — written and verbal
• Cross-functional communication
• Ownership mindset — takes accountability end-to-end
• High motivation to learn and grow in a startup environment

Office/Remote: Remote — any location

Project tasks:

• Build and maintain ELT data pipelines for game and product data
• Develop, test, and document dbt models following analytics engineering best practices
• Work with Google BigQuery for analytics, optimization, and cost efficiency
• Write clean Python for data processing and automation
• Ensure data quality, reliability, and consistency across datasets
• Monitor pipelines, troubleshoot issues, take ownership of fixes end-to-end
• Contribute to data architecture decisions in a fast-paced startup environment

English level: Upper-Intermediate / Advanced